The present invention relates to signal processing and more specifically to the normalization of a plurality of signals having a shared component.
In many signal processing applications, a plurality of signals may exist having a shared component. One or more of these related signals may become distorted in a nonlinear manner. In some applications, each signal may be distorted in a different way or not at all and the nature of the distortion may not be predictable. In addition, it may be difficult to determine which of the related signals has become distorted. Such distortion is normally undesirable.
For example, in the field of image processing, digital images may suffer from nonlinear distortion, whether those images be scanned photographic images, satellite images, medical images, or other types of digital images. Such distortion may be present in an analog representation of the image and/or may occur during the creation of the digital image. In the scanning of photographic images, for example, the three color channels of a typical digital image may each suffer nonlinear distortion during the scanning process, but such nonlinear distortion may be different in each color channel. Such nonlinear distortion may degrade the image in an undesirable way. For photographic images, the image may not look as pleasing to the eye. For satellite images and medical images, the information provided by the image may not be as useful due to such distortion.
One aspect of the invention is a method for normalizing a plurality of signals having a shared component wherein at least one of the plurality of signals has been distorted in a nonlinear way. A distortion function is determined for at least one of the plurality of signals wherein the distortion function is proportional to the distortion of a particular signal relative to at least one of the remaining signals. An inverse relative distortion function may be generated for the signal wherein such function is responsive to the distortion function that was determined for the signal. The signal in question may then be normalized by applying the inverse relative distortion function that was generated for that signal.
The invention has several important technical advantages. Various embodiments of the invention may have none, one, some, or all of these advantages without departing from the scope of the invention. The invention allows signals having a shared component wherein one or more of those signals has been distorted in a nonlinear way to automatically be normalized with respect to one another. Although the distortion may not be entirely removed, the signals may more accurately represent the desired signal. The invention may advantageously be employed in the area of image processing. For example, the invention may be used to correct distortion in the color channels of a digital image representative of a color photographic image. The color channels may be normalized such that the overall image is enhanced and the colors of the image appear more pleasing to the eye. For satellite images and medical images, the invention may be used to enhance the accuracy and usefulness of information provided by the image. Because the invention may employ a computer and/or scanner to perform such normalization, the invention allows automated normalization of images. Such automated normalization may reduce the time and effort needed to achieve such normalization and allow normalization of a greater number of images. For example, in the case of photographic images, it may be possible to correct nonlinear distortion manually using software such as Photoshop. The invention may allow automated color correction of any desired image at a fraction of the time, at a fraction of the cost, and without specialized knowledge being employed by the person correcting the image.